Local weather scenarios for soil and crop models: a simple generator based on historic data sampling

Abstract. Weather scenarios are for example required to model future agricultural production and the development of soil properties under climate change. These scenarios should realistically depict regional weather conditions at a daily resolution for the expected climate development. In this technical note, we present the LocalWeatherSampler (LWS) for generating mid-term weather scenarios (20–30 years) for specific regions or locations based on historically recorded weather data. It is demonstrated for an example site in Germany. The core idea is to define wet or dry years and to increase their abundance in future years via a random sampling from history. A temperature trend based on common climate projections can be added afterwards. For the definition of dry/wet years, two different methods are implemented. The historical weather data can be either divided manually into a pool of wet (or dry) years or based on the Standardized Precipitation Index (SPI). By varying the threshold value for wet (dry) years and their probability of appearance within the scenario, the framework allows for the generation of scenarios tailored to specific requirements, such as sequences characterized by extremely dry years or by moderately dry years, as well as extremely wet future sequences. This approach is designed to test or analyze future scenarios of precipitation regimes and temperature trends using models that require realistic daily weather data, such as soil, crop, or hydrological models.